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license: apache-2.0 |
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# Korean Character BERT Model (small) |
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Welcome to the repository of the Korean Character (syllable-level) BERT Model, a compact and efficient transformer-based model designed specifically for Korean language processing tasks. This model takes a unique approach by tokenizing text at the syllable level, catering to the linguistic characteristics of the Korean language. |
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## Features |
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- Vocabulary Size: The model utilizes a vocabulary of 7,477 tokens, focusing on Korean syllables. This streamlined vocabulary size allows for efficient processing while maintaining the ability to capture the nuances of the Korean language. |
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- Transformer Encoder Layers: It employs a simplified architecture with only 3 transformer encoder layers. This design choice strikes a balance between model complexity and computational efficiency, making it suitable for a wide range of applications, from mobile devices to server environments. |
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- License: This model is open-sourced under the Apache License 2.0, allowing for both academic and commercial use while ensuring that contributions and improvements are shared within the community. |
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## Getting Started |
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```python |
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# Load model directly |
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from transformers import AutoTokenizer, AutoModelForMaskedLM |
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tokenizer = AutoTokenizer.from_pretrained("MrBananaHuman/char_ko_bert_small") |
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model = AutoModelForMaskedLM.from_pretrained("MrBananaHuman/char_ko_bert_small") |
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``` |
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## Fine-tuning example |
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- [Named entity recognition](https://colab.research.google.com/drive/1WirfVhJIbKH70stuLRPhiPr2CexZiGuP?usp=sharing) |
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## Contact |
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For any questions or inquiries, please reach out to me at mrbananahuman.kim@gmail.com |
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I'm always happy to discuss the model, potential collaborations, or any other inquiries related to this project. |
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